AI Engineer III – AI Enablement

Consistent with CareSource’s AI Engineer III career level, this role operates independently on complex, ambiguous problems; sets technical direction within its domain; and leads design and delivery without day-to-day oversight.

This role does not own or operate core AI platforms or runtime infrastructure. You will partner closely with AI Platform, Infrastructure, and SRE teams by providing solution requirements, architectural input, and design feedback while maintaining a clear separation between solution design (AITE) and platform delivery and operations.

Technical leadership and solution architecture

• Lead solution-level architecture for AI initiatives, including data, models, orchestration, security, integration, and observability
• Define and maintain reference architectures, design patterns, and technical standards for AI-enabled solutions
• Translate business problems into actionable designs and clearly communicate tradeoffs, risks, and constraints
• Provide technical decision support and recommendations to AI and IT leadership

Hands-on engineering and validation

• Build proofs of concept and pilots, and implement critical solution components to de-risk delivery
• Develop and validate RAG pipelines, agent-based architectures, and orchestration workflows
• Contribute production-quality code and configurations when hands-on intervention is needed to unblock delivery
• Evaluate emerging AI capabilities, tools, and services through targeted experimentation

Enablement, guidance, and oversight

• Provide technical guidance to delivery teams, architects, and engineers implementing AI solutions
• Conduct architecture and design reviews to ensure alignment with enterprise architecture, security, and governance standards
• Mentor engineers and architects on AI design patterns, implementation practices, and operational considerations
• Review vendor-proposed designs and implementations for alignment with CareSource standards

AITE automation and enablement capabilities

• Design, develop, and implement internal automations that support AITE intake, governance workflows, reporting, and operational visibility
• Translate documented process specifications into durable, reusable automation capabilities
• Own the technical design and evolution of AITE’s internal enablement tooling as the team expands
• Architect automation solutions to scale with increased AI demand, additional governance requirements, and broader AITE scope

Governance and Responsible AI by design

• Embed governance and Responsible AI requirements into solution architectures from inception
• Partner with Security, Risk, Legal, and AI Governance stakeholders to ensure compliant implementations
• Define solution-level controls for data protection, auditability, and appropriate human oversight

Platform partnership (non-operational)

• Provide solution-driven requirements and architectural feedback to AI Platform and Infrastructure teams
• Collaborate on standards for LLMOps, observability, reliability, and cost management without owning platform operations

Education and experience

• Bachelor’s degree in Computer Science, Engineering, or a related technical field required; equivalent experience accepted in lieu of degree
• 7+ years of hands-on software or systems engineering experience
• 3+ years designing and implementing AI-enabled or advanced analytics solutions in an enterprise environment
• Demonstrated experience acting as a senior technical lead across multiple teams and stakeholders

Technical skills and expertise

• AI solution architecture: strong grasp of modern AI patterns including RAG, agentic workflows, orchestration layers, and evaluation approaches
• Hands-on engineering: strong Python skills and modern software engineering practices (testing, version control, CI/CD as applicable)
• Azure AI ecosystem: experience designing solutions using Azure AI Services (Azure OpenAI, AI Search, Azure Machine Learning, Azure AI Foundry)
• Integration and APIs: ability to design secure, scalable system integrations
• Security-aware design: working knowledge of identity, network isolation, private endpoints, and enterprise security constraints
• Evaluation and observability: ability to define success metrics and interpret performance, cost, latency, and reliability signals
• Automation engineering (AITE-owned): experience designing workflow automation and operational tooling (for example, Power Platform, SharePoint, and service workflow integrations)

Leadership and communication

• Ability to explain technical concepts and tradeoffs to technical and non-technical audiences
• Strong written documentation skills for architectures, standards, and technical guidance
• Comfort influencing across organizational boundaries without direct authority

Certifications (Preferred)

• Microsoft Certified: Azure AI Engineer Associate or equivalent
• Azure Solutions Architect Expert (preferred)

• General office environment; hybrid-eligible
• Occasional extended periods of sitting or standing
• Travel not typically required

Compensation Range:

CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.

Compensation Type (hourly/salary):

Organization Level Competencies

• Fostering a Collaborative Workplace Culture

• Cultivate Partnerships

• Develop Self and Others

• Drive Execution

• Influence Others

• Pursue Personal Excellence

• Understand the Business